摘要：
Food and water security are critical challenges in Pakistan, exacerbated by rapid population growth, climate variability, and limited resources. This study explores the application of machine learning techniques to address these issues. We specifically examine the dimensions of food and water security in Pakistan, employing data-driven methods to enhance crop yield predictions, food production forecasting, and water resource management. Using secondary data, we refine machine learning models, such as random forest and linear regression, to analyze water availability, crop yield, and crop production. These models aim to optimize resource distribution, improve irrigation efficiency, and minimize water waste. We propose developing AI-based predictions to address food and water crises proactively. Our findings indicate that food insecurity persists in Pakistan, worsened by uneven distribution. Given the country's high dependence on irrigation for crop production, we analyze the impact of population growth on food production and water demand. We recommend a comprehensive strategy that includes infrastructure development, improved water use efficiency in agriculture, and policy adjustments to balance food imports and exports.
期刊：
FRONTIERS IN PLANT SCIENCE,2025年16:1486575 ISSN：1664-462X
通讯作者：
Wang, Jun;Yan, WD
作者机构：
[Farooq, Asma; Wang, Guangjun; Wang, Jun; Farooq, Taimoor Hassan; Yuan, Chenglin; Yan, Wende; Zeng, Yan; Li, Wang] Cent South Univ Forestry & Technol, Natl Engn Lab Appl Technol Forestry & Ecol South C, Changsha, Hunan, Peoples R China.;[Farooq, Taimoor Hassan] Cent South Univ Forestry & Technol, Bangor Coll, Changsha, Hunan, Peoples R China.;[Fang, Yingchun] Hunan Engn & Technol Res Ctr Heavy Pollut Ind Wast, Changsha, Hunan, Peoples R China.
通讯机构：
[Wang, J; Yan, WD ] C;Cent South Univ Forestry & Technol, Natl Engn Lab Appl Technol Forestry & Ecol South C, Changsha, Hunan, Peoples R China.
关键词：
ecological integrity;heavy metal;soil pollution;livestock manure;passivation remediation;cleaner production
摘要：
The upper reaches of the Taojia River have been impacted by unregulated logging linked to non-ferrous metal mining, resulting in significant mineral waste accumulation. Composting has shown promise in reducing heavy metal (HM) contamination in agricultural soils. This study included two segments: the first examined the effects of sheep manure (SM) and chicken manure (CM) with different concentrations on lead (Pb) dynamics in vegetable soils. The second applied the most effective method identified in segment one to assess Pb, cadmium (Cd), zinc (Zn), and copper (Cu) in soil, paddy, and straw in rice fields. Results showed that both compost types increased soil pH to mildly alkaline levels, with SM causing dose-dependent rises (insignificant between 2% and 5%) and CM inducing non-proportional alkalinity. CM compost significantly enhanced soil organic matter (SOM: 0.606–0.660 g/kg) compared to SM (0.414–0.495 g/kg). Total nitrogen (TN) spiked at 2% SM (0.172 g/kg) but plateaued until 10% SM (0.210 g/kg), while CM linearly increased TN with dosage. Total phosphorus (TP) rose proportionally with SM but remained unchanged under CM. For Pb immobilization, 5% SM reduced DTPA-Pb to 11.877 mg/kg, but 10% SM increased it (14.006 mg/kg), whereas 10% CM achieved optimal passivation (11.561 mg/kg). Correlation analyses linked compost dosage to SOM, TP, and available Pb (p < 0.05), with soil pH showing minimal direct influence. In rice fields, 10% CM elevated soil pH (7.10 vs. 6.71), TP, and total Zn/Cu/Pb/Cd but reduced Pb/Cd in paddy and straw. Heavy metal speciation revealed strong inter-state correlations (excluding exchangeable Pb), with soil pH and TP significantly influencing Zn, Cu, and Cd levels. These findings demonstrate CM compost’s dual role in improving fertility and mitigating Pb/Cd uptake, though Zn/Cu accumulation risks require careful management.
摘要：
Under the "dual carbon" goal, the new quality productivity in the industrial energy sector will become an important force in promoting the green and high-quality development of Hubei Province's economy and society. The article comprehensively uses the Tapio decoupling model and LMDI decomposition method, and empirically analyzes the decoupling effect and driving factors of industrial carbon emissions in Hubei Province from 2006 to 2022 using panel data of industrial industries. Research has found that the growth of Hubei's industrial economy and carbon emissions have undergone a fluctuating process of "strong decoupling → weak decoupling → expansion negative decoupling". For a considerable period of time in the future, the industrial economic growth and carbon emissions in Hubei will still be in a weak or expanding negative decoupling state. From the decomposition results, it can be seen that the trend of changes in the energy intensity index and carbon intensity index shows a high degree of consistency, and the energy intensity index has become the main factor driving the decrease in Hubei's industrial carbon intensity index. However, the impact of energy structure effects and industrial structure effects on industrial carbon emissions is relatively weak, and the dividends brought by structural effects are still not significant. On this basis, the article proposes relevant policy recommendations, providing theoretical basis and policy basis for empowering high-quality industrial development in Hubei Province with new quality productivity in the post epidemic era.
作者机构：
[Ren, Jia] Electronic Information and Physics College, Central South University of Forestry and Technology, Changsha, Hunan 410004, P. R. China;[Radosław Cichocki; Synkiewicz-Musialska, Beata] Łukasiewicz Research Network─Institute of Microelectronics and Photonics, Kraków 30-701, Poland;["Rollo, Andrew; Cameron, Joseph; Dias, Jose Diego Fernandes; Kettle, Jeff"] James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.;Bangor College, Central South University of Forestry and Technology, Changsha, Hunan 410004, P. R. China;[Zhang, Shoushou] James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.<&wdkj&>Bangor College, Central South University of Forestry and Technology, Changsha, Hunan 410004, P. R. China
通讯机构：
[Shoushou Zhang; Jeff Kettle] J;James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.<&wdkj&>Bangor College, Central South University of Forestry and Technology, Changsha, Hunan 410004, P. R. China<&wdkj&>James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.
摘要：
Sustainable food production is one of the key challenges that humanity must overcome to combat global malnutrition and meet the projected increase in the demand for food. Digital agriculture, with the application of sensors to monitor factors such as pH, humidity, and temperature, can improve the efficiency of crop production. However, the sustainability of these devices must be considered. In this work, we report the development of impedance-based pH sensors by using biodegradable materials. It is demonstrated that impedance is an effective way to measure differences in pH using a molybdenum disulfide-based sensor. These sensors can detect agriculturally relevant compounds, as demonstrated by ethephon in this paper, where the active compound's concentration alters the solution's pH. We also demonstrate how the molybdenum disulfide pH sensors can be used with our developed wireless sensor network, which can be used for field measurements, giving good agreement compared to impedance measurements using an electrochemical workstation. Life cycle assessment analysis shows that combining a recyclable wireless sensor network with replaceable and degradable sensors leads to a small environmental footprint. As such, this is a promising approach to digital agriculture, which can contribute to more sustainable food production while minimizing the level of electronic waste generation.
作者：
Muhammad Haroon Shah;Syed Tauseef Hassan*;Irfan Ullah;Yaoyao Wang;Ashfaq Ahmad Shah
期刊：
Gondwana Research,2025年 ISSN：1342-937X
通讯作者：
Syed Tauseef Hassan
作者机构：
[Muhammad Haroon Shah; Yaoyao Wang] Bangor College, Central South University of forestry and technology, Chnagsha, Hunan, China;[Syed Tauseef Hassan] School of Economics and Management, Anhui Polytechnic University, WuHu 241000, China;[Irfan Ullah] Reading Academy, Nanjing University of Information Science and Technology, Nanjing 210044. China;[Ashfaq Ahmad Shah] Research Center for Environment and Society, Hohai University, Nanjing, Jiangsu, China
通讯机构：
[Syed Tauseef Hassan] S;School of Economics and Management, Anhui Polytechnic University, WuHu 241000, China
摘要：
The sustainability of essential resources like water, food, and energy is critical for human well-being and societal development. In the ASEAN context, understanding the relationship between economic growth, water resources, temperature, and bioenergy is crucial for shaping effective policies. This study examines the impact of these factors on the ecological footprint, offering insights into the region’s sustainable resource management. A sustainable ecosystem remains a prerequisite for the efficient exploitation and utilization of these resources By utilizing advanced panel econometrics models such as CUP-BC (Continuously-Updated and Bias-Corrected) and CUP-FM (Continuously-Updated and Fully-Modified), and bolstered by common correlated mean group (CCMG) and augmented mean group (AMG) models to ensure robustness. Additionally, the study reveals that the positive relationship between water resources and temperature contributes to an increase in the ecological footprint. It is worth noting that the bioenergy coefficient, which is both negative and significant, indicates a favorable contribution towards the reduction of ecological footprint. The reliability of the study is highlighted by its consistency across multiple models. Policymakers in South Asian nations must give precedence to the implementation of sustainable water management methods in order to successfully address the increasing ecological impact associated with the interrelationship between water resources and temperature. Findings of the study support the recommendation to encourage the adoption of bioenergy as an effective strategy for decreasing ecological impact and promoting environmental sustainability.
The sustainability of essential resources like water, food, and energy is critical for human well-being and societal development. In the ASEAN context, understanding the relationship between economic growth, water resources, temperature, and bioenergy is crucial for shaping effective policies. This study examines the impact of these factors on the ecological footprint, offering insights into the region’s sustainable resource management. A sustainable ecosystem remains a prerequisite for the efficient exploitation and utilization of these resources By utilizing advanced panel econometrics models such as CUP-BC (Continuously-Updated and Bias-Corrected) and CUP-FM (Continuously-Updated and Fully-Modified), and bolstered by common correlated mean group (CCMG) and augmented mean group (AMG) models to ensure robustness. Additionally, the study reveals that the positive relationship between water resources and temperature contributes to an increase in the ecological footprint. It is worth noting that the bioenergy coefficient, which is both negative and significant, indicates a favorable contribution towards the reduction of ecological footprint. The reliability of the study is highlighted by its consistency across multiple models. Policymakers in South Asian nations must give precedence to the implementation of sustainable water management methods in order to successfully address the increasing ecological impact associated with the interrelationship between water resources and temperature. Findings of the study support the recommendation to encourage the adoption of bioenergy as an effective strategy for decreasing ecological impact and promoting environmental sustainability.
作者机构：
[Tian, Yunlong; Wu, Pengfei; Li, Linxin; Xu, Jingjing; Ma, Xiangqing] College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China;[Tian, Yunlong; Wu, Pengfei; Li, Linxin; Xu, Jingjing; Ma, Xiangqing] Chinese Fir Engineering Technology Research Center of the State Forestry and Grassland Administration, Fuzhou, Fujian, China;[Farooq, Taimoor Hassan] Bangor College, Central South University of Forestry and Technology, Changsha, Hunan, China
期刊：
Energy Economics,2024年136:107713 ISSN：0140-9883
通讯作者：
Wu, ZG
作者机构：
[Li, Di] City Univ Macau, Fac Finance, Macau, Peoples R China.;[Wu, Zhige] Cent South Univ Forestry & Technol, Coll Econ, Res Ctr High Qual Dev Ind Econ, Changsha, Peoples R China.;[Tang, Yixuan] Cent South Univ Forestry & Technol, Bangor Coll, Changsha, Peoples R China.;[Li, Di] City Univ Macau, Ave Padre Tomas Pereira Taipa, Macau, Peoples R China.;[Wu, Zhige] 498 Shaoshan Rd South, Changsha, Hunan, Peoples R China.
通讯机构：
[Wu, ZG ] C;Cent South Univ Forestry & Technol, Coll Econ, Res Ctr High Qual Dev Ind Econ, Changsha, Peoples R China.;498 Shaoshan Rd South, Changsha, Hunan, Peoples R China.
关键词：
Clean energy stock prices;Dirty energy stock prices;Dynamic conditional correlations;Climate risks
摘要：
Prior studies have extensively exhibited an interest in exploring the connectedness between dirty and clean energy stock prices alongside the drivers of such price connectedness, shedding light on hedging strategies for finance practitioners. Nevertheless, no empirical research has examined whether climate risks, the emerging indicator for investors to handle the divestment of dirty energy stocks, have affected the time-varying dirty–clean energy equity price nexus. This study fills this gap by innovatively identifying dynamic conditional correlations (DCCs) between dirty and clean energy stock prices. An ARDL/NARDL model is applied to assess whether the climate risks affect such correlations by controlling for business cycles, funding liquidity, USD values, and oil market sentiments. Overall, we detect an undeniable negative impact of climate risks on the positive dirty–clean energy price dynamic correlations. Additionally, the NARDL model results reveal that a rise in federal fund rates exerts higher effects on the dirty–clean energy stock price comovements. Our findings suggest the strengthened potential of hedging clean energy stocks against dirty energy equities in case of escalating climate risks and heightened fossil fuel price volatilities. Furthermore, substantial attention is required to account for monetary policies' asymmetric effects on clean energy investment.
Prior studies have extensively exhibited an interest in exploring the connectedness between dirty and clean energy stock prices alongside the drivers of such price connectedness, shedding light on hedging strategies for finance practitioners. Nevertheless, no empirical research has examined whether climate risks, the emerging indicator for investors to handle the divestment of dirty energy stocks, have affected the time-varying dirty–clean energy equity price nexus. This study fills this gap by innovatively identifying dynamic conditional correlations (DCCs) between dirty and clean energy stock prices. An ARDL/NARDL model is applied to assess whether the climate risks affect such correlations by controlling for business cycles, funding liquidity, USD values, and oil market sentiments. Overall, we detect an undeniable negative impact of climate risks on the positive dirty–clean energy price dynamic correlations. Additionally, the NARDL model results reveal that a rise in federal fund rates exerts higher effects on the dirty–clean energy stock price comovements. Our findings suggest the strengthened potential of hedging clean energy stocks against dirty energy equities in case of escalating climate risks and heightened fossil fuel price volatilities. Furthermore, substantial attention is required to account for monetary policies' asymmetric effects on clean energy investment.
通讯机构：
[Lin, Y ] C;Cent South Univ Forestry & Technol, Bangor Coll, Changsha 410004, Peoples R China.
关键词：
East Dongting lake;Land use;Landscape pattern;Species diversity;Vegetation coverage
摘要：
Exploring the impact factors associated with biodiversity and the relationship between them has always been a concerned issue in recent years. However, the previous research mostly focus on theoretical layer. Accordingly, the relationship between landscape pattern and biodiversity is to be analyzed in this research. The landscape pattern determines the function and ecological process of the landscape, and affects the species flow, information flow and energy flow in the landscape. Land use patterns has inevitably left an impact on the landscape pattern. Landscape pattern determines the function and ecological process of landscape and thus plays a significant role in biodiversity. East Dongting Lake National Nature Reserve is taken as the research object of the paper, and the remote sensing image data of three different time periods are collected, including 2000, 2010 and 2020. With an interpretation of the vegetation landscape pattern changes inside the protected area to collect and analyze the vegetation coverage. By comparing landscape patterns and the dynamic changes of land use in different periods of time, the correlation between landscape pattern characteristics and regional biodiversity is to be analyzed. Research shows: (1) From 2000 to 2020, the vegetation coverage of East Dongting Lake increased, but the landscape shape, scale, diversity and uniformity index decreased to varying degrees. (2) At the class level of landscape type, the relationship between landscape index and biodiversity is different. A complex relationship between farmland landscape and biodiversity. There is a significant positive correlation between the index of grassland landscape type and the index of regional biodiversity. (3) The correlation analysis results at the landscape level show that the landscape characteristic index is positively correlated with the regional biodiversity index. The grassland landscape in the area is the main habitat of biological species. At the same time, as the main grain producing area, the impact of farmland landscape cannot be ignored. This study has certain theoretical guiding significance for the protection and management of biodiversity in the region in terms of maintaining landscape pattern in particular the grassland landscape area and increasing vegetation coverage in the process of land use.
摘要：
The coupling and coordination of high-quality agricultural development (HQAD) and rural revitalization is an inevitable choice to accelerate the realization of Chinese-style agricultural and rural modernization. Based on system theory, this study reconstructs the indicator systems of both and conducts measurements by applying the improved AHP-entropy weight method. This study has extended the analytical methods of kernel density estimation, Dagum Gini coefficient, sigma convergence, and spatial beta convergence to further investigate the spatio-temporal evolution, regional disparities, and convergence effect of the coupling coordination degree (CCD) of HQAD and rural revitalization in China from 2010 to 2020. The results show that the CCD has a tendency to increase year by year, presenting the characteristics of 'high coupling degree-low comprehensive development level-low coupling coordination degree', and also has the spatial distribution pattern of 'high in the east and low in the west'. In addition, most of the provinces have a tendency to jump to a higher stage of coupling coordination; the overall trend of the kernel density curves is favorable; the results of Dagum's Gini coefficient show that inter-regional disparities contribute the most to regional spatial disparities; and there is a significant tendency towards sigma convergence and spatial beta convergence of the CCD in China and the four regions. This study stimulates a broader discussion of rural revitalization, with potential implications for decision making in practice.
作者机构：
[Wu, Mingbao; Wan, Fangying; Li, Yong; Zheng, Z; Zheng, Zhian] Cent South Univ Forestry & Technol, Coll Elect Informat & Phys, Changsha, Hunan, Peoples R China.;[Yu, Yi] Cent South Univ Forestry & Technol, Coll Bangor, Changsha 410004, Hunan, Peoples R China.;[Lin, Yanhua] Cent South Univ Forestry & Technol, Coll Foreign Languages, Changsha 410004, Hunan, Peoples R China.
通讯机构：
[Zheng, Z ] C;Cent South Univ Forestry & Technol, Coll Elect Informat & Phys, Changsha, Hunan, Peoples R China.
关键词：
Polar code;Orthogonal frequency division multiplexing (OFDM);Multipath fading channel;Channel state information;Packet interleaving
摘要：
In this paper, we investigate the decoding performance and corresponding decoding strategies for polar-coded orthogonal frequency division multiplexing (OFDM) system operating under multipath fading channels. Multipath fading channels lead to frequency selective fading of the OFDM signal, resulting in varying levels of noise interference across different subcarriers after equalization. Furthermore, frequency selective fading induces burst errors in the equalized information, thereby significantly degrading the decoding performance. To address these issues, we propose two schemes in this paper to enhance the decoding performance of polar-coded OFDM system. Firstly, we integrate the channel state information of each subcarrier into the generation of soft information for the polar codes decoder, in order to alleviate the degradation of decoding performance caused by variations in signal-to-noise ratio across subcarriers during OFDM demodulation. Secondly, we introduce a packet interleaving design after the polar codes encoder to enhance the robustness of polar codes against burst errors. Simulation results demonstrate that the combined application of these two decoding strategies significantly outperforms the conventional scheme in terms of transmission performance over multipath fading channels. The findings of this study suggest that, within the context of future wireless communication systems utilizing Polar-OFDM, the concurrent implementation of our two proposed decoding strategies is essential for achieving robust error correction performance in the OFDM system.
摘要：
Indium-gallium–zinc-oxide thin-film transistors (IGZO TFTs) are widely used in numerous applications including displays and are emerging as a promising alternative for flexible IC production due to their high transparency, superior field-effect mobility, and low-temperature processability. However, their stability under different voltage stresses remains a concern, primarily due to carrier trapping in the gate dielectric and point defect creation. This study involves the fabrication of IGZO TFTs and their subsequent bias stress testing in linear and saturation regions. The impact of a passivation layer on top of the active channel is investigated to mitigate bias stress susceptibility. The passivated thin-film transistors (TFTs) exhibit reduced bias stress susceptance, with $\Delta {V}_{T}$ only moderately affected by the positive gate-bias stress (PGBS). This suggests that fewer electrons are being trapped at the interface between the dielectric/semiconductor. Conventional bias stress testing methods for TFTs are time-consuming and depend on air-stable devices. To address this, we introduce a “voltage step-stress” (VSS) approach. This method offers an accelerated way to conduct bias stress measurements without compromising test accuracy, reducing testing time by 8 hours (a 45% relative reduction).
作者：
Rollo, Andrew C.;Zang, Shoushou;Cameron, Joseph;Jia, Ren;Kettle, Jeff
期刊：
2024 IEEE INTERNATIONAL FLEXIBLE ELECTRONICS TECHNOLOGY CONFERENCE, IFETC 2024,2024年:1-3
通讯作者：
Rollo, AC
作者机构：
[Kettle, Jeff; Rollo, Andrew C.; Cameron, Joseph] Univ Glasgow, James Watt Sch Engn, Glasgow, Lanark, Scotland.;[Zang, Shoushou] Cent South Univ Forestry & Technol, Bangor Coll, Changsha, Peoples R China.;[Jia, Ren] Cent South Univ Forestry & Technol, Sch Elect & Phys, Changsha, Peoples R China.
通讯机构：
[Rollo, AC ] U;Univ Glasgow, James Watt Sch Engn, Glasgow, Lanark, Scotland.
会议名称：
2024 IEEE International Flexible Electronics Technology Conference (IFETC)
会议时间：
15 September 2024
会议地点：
Bologna, Italy
会议主办单位：
[Rollo, Andrew C.;Cameron, Joseph;Kettle, Jeff] Univ Glasgow, James Watt Sch Engn, Glasgow, Lanark, Scotland.^[Zang, Shoushou] Cent South Univ Forestry & Technol, Bangor Coll, Changsha, Peoples R China.^[Jia, Ren] Cent South Univ Forestry & Technol, Sch Elect & Phys, Changsha, Peoples R China.
会议论文集名称：
2024 IEEE International Flexible Electronics Technology Conference (IFETC)
摘要：
This paper presents a wireless and handheld pH measurement system with a flexible, detachable and degradable pH sensor. All materials that form the pH sensor materials have been selected so that they are degradable and form non-toxic and benign materials at the end of life. The pH sensors, once integrated with a Wireless Sensor Network (WSN), enable real-time monitoring of pH levels and autonomous data collection. The degradable sensors align with UN sustainability goals, reducing environmental impact and encouraging reuse of electronics and responsible disposal practices.
作者机构：
[Zhang, Tianwei; Harwell, Jonathon; Wagih, Mahmoud; Bainbridge, Andrew; Kettle, Jeff] Univ Glasgow, James Watt Sch Engn, Glasgow City G12 8QQ, Scotland.;[Zhang, Shoushou] Cent South Univ Forestry & Technol, Bangor Coll, Changsha, Peoples R China.
通讯机构：
[Zhang, TW ] U;Univ Glasgow, James Watt Sch Engn, Glasgow City G12 8QQ, Scotland.
关键词：
IC recycling;LCA;PCB assembly;Sustainable electronics
摘要：
As consumer microelectronics become ever more ubiquitous, there are growing concerns about their environmental impact. However, the diversity of designs and components used in modern devices makes a coherent mitigation strategy hard to formulate. In this work, we perform a quantitative life cycle assessment (LCA) of the environmental profiles of both high-value (a smartwatch) and low-value (a TV remote) devices and find that the optimal mitigation strategy varies substantially between these two extremes. We find that the impact of the smartwatch is dominated by the production costs of its integrated circuits (ICs), and so a priority on device lifetime and design-for-recycling of the ICs is the best path to minimizing impact. On the other hand, the TV remote's impact is dominated by the cost of its fiberglass (FR4) substrate, with the much simpler ICs playing a much smaller role. Our results show that the impact of low-cost devices is best mitigated by incorporating eco-friendly substrates and additive manufacturing techniques, while also minimizing the use of critical raw materials (CRMs). These results will help guide future industrial strategies, and we provide a list of challenges and opportunities in making electronics green.
通讯机构：
[Tong, J ] C;Cent South Univ Forestry & Technol, Coll Bangor, Changsha 410004, Hunan, Peoples R China.
关键词：
Green finance;Behavior choice of commercial banks;Green -credit policy
摘要：
This paper investigates the impact of green credit on the performance and risk of Chinese commercial banks, and also explores the impact of green technology on this mechanism. The results show that for all banks, green loan balances have a significantly negative impact on net profit. While for large, small and medium sized banks, it also reduces and increases bank insolvency risk respectively. Therefore, our findings suggest that the standard mechanism for measuring the benefits of green credit should be improved and the regulatory mechanism for green credit should be strengthened.
This paper investigates the impact of green credit on the performance and risk of Chinese commercial banks, and also explores the impact of green technology on this mechanism. The results show that for all banks, green loan balances have a significantly negative impact on net profit. While for large, small and medium sized banks, it also reduces and increases bank insolvency risk respectively. Therefore, our findings suggest that the standard mechanism for measuring the benefits of green credit should be improved and the regulatory mechanism for green credit should be strengthened.
作者：
Shah, Wilayat;Chen, Junfei;Ullah, Irfan;Shah, Muhammad Haroon
期刊：
Water,2024年16(11):1492- ISSN：2073-4441
通讯作者：
Ullah, I;Shah, MH
作者机构：
[Shah, Wilayat; Chen, Junfei] Hohai Univ, Business Sch, Nanjing 210098, Peoples R China.;[Ullah, Irfan; Ullah, I] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China.;[Shah, Muhammad Haroon; Shah, MH] Cent South Univ Forestry & Technol, Bangor Coll, Changsha 410018, Peoples R China.;Nanjing Univ Informat Sci & Technol, Reading Acad, Nanjing 211544, Peoples R China.
通讯机构：
[Ullah, I ] H;[Shah, MH ] C;Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China.;Cent South Univ Forestry & Technol, Bangor Coll, Changsha 410018, Peoples R China.
关键词：
RNN-LSTM;water resources;surface water and groundwater;drought prediction;Pakistan
摘要：
Water is a fundamental and crucial natural resource for human survival. However, the global demand for water is increasing, leading to a subsequent decrease in water availability. This study addresses the critical need for improved water resource forecasting models amidst global water scarcity concerns exacerbated by climate change. This study uses the best weather and water resource forecasting model for sustainable development. Employing a Recurrent Neural Network–Long Short-Term Memory (RNN-LSTM) approach, the research enhances drought prediction capabilities by integrating secondary data of the rainfall, temperature, and ground and surface water supplies. The primary objective is to forecast water resources under changing climatic conditions, facilitating the development of early warning systems for vulnerable regions. The results from the LSTM model show an increased trend in temperature and rainfall patterns. However, a relatively unstable decrease in rainfall is observed. The best statistical analysis result was observed with the LSTM model; the model’s accuracy was 99%, showing that it was quite good at presenting the obtained precipitation, temperature, and water data. Meanwhile, the value of the root mean squared error (RMSE) was about 13, 15, and 20, respectively. Therefore, the study’s results highlight that the LSTM model was the most suitable among the artificial neural networks for forecasting the weather, rainfall, and water resources. This study will help weather forecasting, agriculture, and meteorological departments be effective for water resource forecasting.
